现代雷达2012，Vol.34Issue(11)：45-48,4.
基于UKF的单站无源定位改进算法
An Improved Single-Observer Passive Location Algorithm Based on UKF
摘要
Abstract
As the calculation of unscented Kalman filter is large and will divergent because of the numerical calculation error, an improved spherical simplex sampling UKF algorithm based on the singular value decomposition ( SVD) is presented. To avoiding the invalidation caused by errors during computation, the algorithm uses SVD technique to decompose the covariance matrix. To improve the computational efficiency, the algorithm uses spherical simplex sampling strategy to reduce the number of sampling points. Simulation results show that the validity of the proposed algorithm further.关键词
单站无源定位/奇异值分解/超球体采样/无迹卡尔曼滤波Key words
single-observer passive location/singular value decomposition/spherical simplex sampling/unscented Kalman filter分类
信息技术与安全科学引用本文复制引用
黄耀光,李建新,高博..基于UKF的单站无源定位改进算法[J].现代雷达,2012,34(11):45-48,4.基金项目
国家自然科学基金资助项目(No.61171108) （No.61171108）
